The measurement of the APD is one of the methods of acquiring statistical data for calculating the time probability of a received signal with an amplitude greater than a predetermined level, and through statistically observing the received signal, signal characteristics which cannot be instantaneously seen may be observed.
For example, an APD measuring device has been proposed in which an analog-digital converter (hereinafter, simply referred to as an “A/D converter”) converts a received signal into digital data, a filter bank allocates the output of the A/D converter to a plurality of frequency band components, weights the amplitudes of each frequency band component with a desired amount and combines the amplitudes, and a weighted APD receives the output of the filter bank, calculates probability on the basis of the frequency of occurrence of the combined amplitude, and displays the calculated probability on a display unit in various ways (for example, see Patent Document 1).
When the band of the signal to be measured by the APD measuring device is wide, in order to minutely observe the behavior of a temporal signal, it is necessary to sample the signal at a speed that is equal to or greater than twice the highest frequency in the band and observe the signal. In addition, in order to measure the APD of the band, it is necessary to sample the signal at a speed that is equal to or greater than ten times the highest frequency and observe the signal. For example, when the band to be measured is 10 MHz, it is necessary to sample and observe data at a speed that is ten times more than the band, that is, at a speed of 100 M/sec (=10 M×10).
When the APD of the extended data is measured, it is necessary to store and accumulate data using a real-time process. In order to simplify the real-time process, the APD measuring device according to the related art quantizes sampled data with accuracy which does not cause a practical problem, accumulates the frequency of appearance for a predetermined period of time (for example, 1 second), and creates probability density function (PDF) data.
Since the PDF data is generated at a predetermined time interval (for example, at a time interval of 1 second), a process of creating APD statistical data, which is a distribution function obtained by cumulatively adding the PDF data, does not need to be performed in real time, but can be performed at a predetermined time interval. The process can be performed by software processing capable of easily processing a complicated process such as a display process or signal processing that is difficult to implement in hardware.
Software processing has a processing speed lower than hardware, but is advantageous in manufacturing costs and future technical succession. The use of software processing together with hardware processing is an effective means to realize a more complicated process such as a control process or the like including a determiner.
As such, the APD measuring device according to the related art measures the APD using two processes, that is, a real-time process and a non-real-time process. The real-time process is performed by hardware and the non-real-time process is performed by software.
In the hardware, a received signal is separated into an in-phase (hereinafter, simply referred to as “I”) component and a quadrature-phase (hereinafter, simply referred to as “Q”) component, an envelope is detected, and logarithmic conversion is performed.
When a signal level is counted at an interval of 0.1 dB, 1000 counters are prepared, and a signal history is accumulated at an interval of 0.1 dB in a dynamic range of 100 dB. Similarly, when the signal level is counted at an interval of 0.05 dB, 2000 counters are prepared and a signal history is accumulated at an interval of 0.05 dB in a dynamic range of 100 dB.
The counters need to be prepared for each frequency band component. For example, when it is assumed that the sampling period is 100 M/s and the quantized levels of the counters are 1000 stages, a maximum count value of 100 M×1000 is transmitted from hardware to the software processing side for one second. An integer value up to 100 M can be represented by 28 bits. Therefore, in this example, the count value for each frequency band component is transmitted at a rate of 28×1000=28 kb/s. When time-series data is transmitted after envelope detection, the count value is transmitted at a rate of 100 M/s×16 bits (16 bits per sample) for 1 second and a transmission rate of 1.6 Gb/s is needed.